Exploratory Review of the Takotsubo Syndrome and the Possible Role of the Psychosocial Stress Response and Inflammaging.

Takotsubo syndrome (TTS) is a cardiomyopathy that clinically presents as a transient and reversible left ventricular wall motion abnormality (LVWMA). Recovery can occur spontaneously within hours or weeks. Studies have shown that it mainly affects older people. In particular, there is a higher prevalence in postmenopausal women. Physical and emotional stress factors are widely discussed and generally recognized triggers. In addition, the hypothalamic-pituitary-adrenal (HPA) axis and the associated glucocorticoid-dependent negative feedback play an important role in the resulting immune response. This review aims to highlight the unstudied aspects of the trigger factors of TTS. The focus is on emotional stress/chronic unpredictable mild stress (CUMS), which is influenced by estrogen concentration and noradrenaline, for example, and can lead to changes in the behavioral, hormonal, and autonomic systems. Age- and gender-specific aspects, as well as psychological effects, must also be considered. We hypothesize that this leads to a stronger corticosteroid response and altered feedback of the HPA axis. This may trigger proinflammatory markers and thus immunosuppression, inflammaging, and sympathetic overactivation, which contributes significantly to the development of TTS. The aim is to highlight the importance of CUMS and psychological triggers as risk factors and to make an exploratory proposal based on the new knowledge. Based on the imbalance between the sympathetic and parasympathetic nervous systems, transcutaneous vagus nerve stimulation (tVNS) is presented as a possible new therapeutic approach.

Structural correlates of language processing in primary progressive aphasia.

Understanding the relationships between brain structure and language behaviour in primary progressive aphasia provides crucial information about these diseases' pathomechanisms. However, previous investigations have been limited from providing a statistically reliable view of broad language abilities by sample size, variant focus and task focus. In this study, the authors aimed to determine the relationship between brain structure and language behaviour in primary progressive aphasia, to determine the degree to which task-associated regions were atrophied across disease variants and to determine the degree to which task-related atrophy overlaps across disease variants. Participants were 118 primary progressive aphasia patients and 61 healthy, age-matched controls tested from 2011 to 2018 in the German Consortium for Frontotemporal Lobar Degeneration cohort. Diagnosis of primary progressive aphasia required progressive deterioration of mainly speech and language for ≥ 2 years, and variant was diagnosed by the criteria of Gorno-Tempini et al. (Classification of primary progressive aphasia and its variants. Neurology. 2011;76(11):1006-1014). Twenty-one participants not fulfilling a specific subtype were classified as mixed-variant and excluded. Language tasks of interest included the Boston naming test, a German adaptation of the Repeat and Point task, phonemic and category fluency tasks and the reading/writing subtest of the Aachen Aphasia Test. Brain structure was measured by cortical thickness. We observed networks of language task-associated temporal, frontal and parietal cortex. Overlapping task-associated atrophy was observed in the left lateral, ventral and medial temporal lobes, middle and superior frontal gyri, supramarginal gyrus and insula. Some regions, primarily in the perisylvian region, were associated with language behaviour despite showing no significant atrophy. The results crucially extend less powerful studies associating brain and language measures in primary progressive aphasia. Cross-variant atrophy in task-associated regions suggests partially shared underlying deficits, whereas unique atrophy reinforces variant-specific deficits. Language task-related regions that are not obviously atrophied suggest regions of future network disruption and encourage understanding of task deficits beyond clearly atrophied cortex. These results may pave the way for new treatment approaches.

Multiclass prediction of different dementia syndromes based on multi-centric volumetric MRI imaging.

INTRODUCTION: Dementia syndromes can be difficult to diagnose. We aimed at building a classifier for multiple dementia syndromes using magnetic resonance imaging (MRI). METHODS: Atlas-based volumetry was performed on T1-weighted MRI data of 426 patients and 51 controls from the multi-centric German Research Consortium of Frontotemporal Lobar Degeneration including patients with behavioral variant frontotemporal dementia, Alzheimer's disease, the three subtypes of primary progressive aphasia, i.e., semantic, logopenic and nonfluent-agrammatic variant, and the atypical parkinsonian syndromes progressive supranuclear palsy and corticobasal syndrome. Support vector machine classification was used to classify each patient group against controls (binary classification) and all seven diagnostic groups against each other in a multi-syndrome classifier (multiclass classification). RESULTS: The binary classification models reached high prediction accuracies between 71 and 95% with a chance level of 50%. Feature importance reflected disease-specific atrophy patterns. The multi-syndrome model reached accuracies of more than three times higher than chance level but was far from 100%. Multi-syndrome model performance was not homogenous across dementia syndromes, with better performance in syndromes characterized by regionally specific atrophy patterns. Whereas diseases generally could be classified vs controls more correctly with increasing severity and duration, differentiation between diseases was optimal in disease-specific windows of severity and duration. DISCUSSION: Results suggest that automated methods applied to MR imaging data can support physicians in diagnosis of dementia syndromes. It is particularly relevant for orphan diseases beside frequent syndromes such as Alzheimer's disease.

Relationship of serum beta-synuclein with blood biomarkers and brain atrophy.

BACKGROUND: Recent data support beta-synuclein as a blood biomarker to study synaptic degeneration in Alzheimer's disease (AD). METHODS: We provide a detailed comparison of serum beta-synuclein immunoprecipitation - mass spectrometry (IP-MS) with the established blood markers phosphorylated tau 181 (p-tau181) (Simoa) and neurofilament light (NfL) (Ella) in the German FTLD consortium cohort (n = 374) and its relation to brain atrophy (magnetic resonance imaging) and cognitive scores. RESULTS: Serum beta-synuclein was increased in AD but not in frontotemporal lobar degeneration (FTLD) syndromes. Beta-synuclein correlated with atrophy in temporal brain structures and was associated with cognitive impairment. Serum p-tau181 showed the most specific changes in AD but the lowest correlation with structural alterations. NfL was elevated in all diseases and correlated with frontal and temporal brain atrophy. DISCUSSION: Serum beta-synuclein changes differ from those of NfL and p-tau181 and are strongly related to AD, most likely reflecting temporal synaptic degeneration. Beta-synuclein can complement the existing panel of blood markers, thereby providing information on synaptic alterations. HIGHLIGHTS: Blood beta-synuclein is increased in Alzheimer's disease (AD) but not in frontotemporal lobar degeneration (FTLD) syndromes. Blood beta-synuclein correlates with temporal brain atrophy in AD. Blood beta-synuclein correlates with cognitive impairment in AD. The pattern of blood beta-synuclein changes in the investigated diseases is different to phosphorylated tau 181 (p-tau181) and neurofilament light (NfL).

Comparative analysis of machine learning algorithms for multi-syndrome classification of neurodegenerative syndromes.

IMPORTANCE: The entry of artificial intelligence into medicine is pending. Several methods have been used for the predictions of structured neuroimaging data, yet nobody compared them in this context. OBJECTIVE: Multi-class prediction is key for building computational aid systems for differential diagnosis. We compared support vector machine, random forest, gradient boosting, and deep feed-forward neural networks for the classification of different neurodegenerative syndromes based on structural magnetic resonance imaging. DESIGN, SETTING, AND PARTICIPANTS: Atlas-based volumetry was performed on multi-centric T1-weighted MRI data from 940 subjects, i.e., 124 healthy controls and 816 patients with ten different neurodegenerative diseases, leading to a multi-diagnostic multi-class classification task with eleven different classes. INTERVENTIONS: N.A. MAIN OUTCOMES AND MEASURES: Cohen's kappa, accuracy, and F1-score to assess model performance. RESULTS: Overall, the neural network produced both the best performance measures and the most robust results. The smaller classes however were better classified by either the ensemble learning methods or the support vector machine, while performance measures for small classes were comparatively low, as expected. Diseases with regionally specific and pronounced atrophy patterns were generally better classified than diseases with widespread and rather weak atrophy. CONCLUSIONS AND RELEVANCE: Our study furthermore underlines the necessity of larger data sets but also calls for a careful consideration of different machine learning methods that can handle the type of data and the classification task best.

Clinical manifestations and immunomodulatory treatment experiences in psychiatric patients with suspected autoimmune encephalitis: a case series of 91 patients from Germany.

Autoimmune encephalitis (AE) can rarely manifest as a predominantly psychiatric syndrome without overt neurological symptoms. This study's aim was to characterize psychiatric patients with AE; therefore, anonymized data on patients with suspected AE with predominantly or isolated psychiatric syndromes were retrospectively collected. Patients with readily detectable neurological symptoms suggestive of AE (e.g., epileptic seizures) were excluded. Patients were classified as "probable psychiatric AE (pAE)," if well-characterized neuronal IgG autoantibodies were detected or "possible pAE" (e.g., with detection of nonclassical neuronal autoantibodies or compatible cerebrospinal fluid (CSF) changes). Of the 91 patients included, 21 (23%) fulfilled our criteria for probable (autoantibody-defined) pAE and 70 (77%) those for possible pAE. Among patients with probable pAE, 90% had anti-NMDA receptor (NMDA-R) autoantibodies. Overall, most patients suffered from paranoid-hallucinatory syndromes (53%). Patients with probable pAE suffered more often from disorientation (p < 0.001) and impaired memory (p = 0.001) than patients with possible pAE. Immunotherapies were performed in 69% of all cases, mostly with high-dose corticosteroids. Altogether, 93% of the patients with probable pAE and 80% of patients with possible pAE reportedly benefited from immunotherapies (p = 0.251). In summary, this explorative, cross-sectional evaluation confirms that autoantibody-associated AE syndromes can predominantly manifest as psychiatric syndromes, especially in anti-NMDA-R encephalitis. However, in three out of four patients, diagnosis of possible pAE was based on nonspecific findings (e.g., slight CSF pleocytosis), and well-characterized neuronal autoantibodies were absent. As such, the spectrum of psychiatric syndromes potentially responding to immunotherapies seems not to be limited to currently known autoantibody-associated AE. Further trials are needed.

Utility of the Repeat and Point Test for Subtyping Patients With Primary Progressive Aphasia.

BACKGROUND: Primary progressive aphasia (PPA) may present with three distinct clinical sybtypes: semantic variant PPA (svPPA), nonfluent/agrammatic variant PPA (nfvPPA), and logopenic variant PPA (lvPPA). OBJECTIVE: The aim was to examine the utility of the German version of the Repeat and Point (R&P) Test for subtyping patients with PPA. METHOD: During the R&P Test, the examiner reads out aloud a noun and the participants are asked to repeat the word and subsequently point to the corresponding picture. Data from 204 patients (68 svPPA, 85 nfvPPA, and 51 lvPPA) and 33 healthy controls were analyzed. RESULTS: Controls completed both tasks with >90% accuracy. Patients with svPPA had high scores in repetition (mean=9.2±1.32) but low scores in pointing (mean=6±2.52). In contrast, patients with nfvPPA and lvPPA performed comparably in both tasks with lower scores in repetition (mean=7.4±2.7 for nfvPPA and 8.2±2.34 for lvPPA) but higher scores in pointing (mean=8.9±1.41 for nfvPPA and 8.6±1.62 for lvPPA). The R&P Test had high accuracy discriminating svPPA from nfvPPA (83% accuracy) and lvPPA (79% accuracy). However, there was low accuracy discriminating nfvPPA from lvPPA (<60%). CONCLUSION: The R&P Test helps to differentiate svPPA from 2 nonsemantic variants (nfvPPA and lvPPA). However, additional tests are required for the differentiation of nfvPPA and lvPPA.

Factors associated with dropout in the longitudinal Vogel study of cognitive decline.

Dementia, including Alzheimer's disease, is a growing problem worldwide. Prevention or early detection of the disease or a prodromal cognitive decline is necessary. By means of our long-term follow-up 'Vogel study', we aim to predict the pathological cognitive decline of a German cohort (mean age was 73.9 ± 1.55 years at first visit) with three measurement time points within 6 years per participant. Especially in samples of the elderly and subjects with chronic or co-morbid diseases, dropouts are one of the biggest problems of long-term studies. In contrast to the large number of research articles conducted on the course of dementia, little research has been done on the completion of treatment. To ensure unbiased and reliable predictors of cognitive decline from study completers, our objective was to determine predictors of dropout. We conducted multivariate analyses of covariance and multinomial logistic regression analyses to compare and predict the subject's dropout behaviour at the second visit 3 years after baseline (full participation, partial participation and no participation/dropout) with neuropsychiatric, cognitive, blood and lifestyle variables. Lower performance in declarative memory, attention and visual-spatial processing predicted dropout rather than full participation. Lower performance in visual-spatial processing predicted partial participation as opposed to full participation. Furthermore, lower performance in mini-mental status examination predicted whether subjects dropped out or participated partially instead of full participation. Baseline cognitive parameters are associated with dropouts at follow-up with a loss of impaired participants. We expect a bias into a healthier sample over time.

Measurement invariance testing of longitudinal neuropsychiatric test scores distinguishes pathological from normative cognitive decline and highlights its potential in early detection research.

OBJECTIVE: Alzheimer's disease (AD) is a growing challenge worldwide, which is why the search for early-onset predictors must be focused as soon as possible. Longitudinal studies that investigate courses of neuropsychological and other variables screen for such predictors correlated to mild cognitive impairment (MCI). However, one often neglected issue in analyses of such studies is measurement invariance (MI), which is often assumed but not tested for. This study uses the absence of MI (non-MI) and latent factor scores instead of composite variables to assess properties of cognitive domains, compensation mechanisms, and their predictability to establish a method for a more comprehensive understanding of pathological cognitive decline. METHODS: An exploratory factor analysis (EFA) and a set of increasingly restricted confirmatory factor analyses (CFAs) were conducted to find latent factors, compared them with the composite approach, and to test for longitudinal (partial-)MI in a neuropsychiatric test battery, consisting of 14 test variables. A total of 330 elderly (mean age: 73.78 ± 1.52 years at baseline) were analyzed two times (3 years apart). RESULTS: EFA revealed a four-factor model representing declarative memory, attention, working memory, and visual-spatial processing. Based on CFA, an accurate model was estimated across both measurement timepoints. Partial non-MI was found for parameters such as loadings, test- and latent factor intercepts as well as latent factor variances. The latent factor approach was preferable to the composite approach. CONCLUSION: The overall assessment of non-MI latent factors may pose a possible target for this field of research. Hence, the non-MI of variances indicated variables that are especially suited for the prediction of pathological cognitive decline, while non-MI of intercepts indicated general aging-related decline. As a result, the sole assessment of MI may help distinguish pathological from normative aging processes and additionally may reveal compensatory neuropsychological mechanisms.

Reduced parietal activation in participants with mild cognitive impairments during visual-spatial processing measured with functional near-infrared spectroscopy.

Functional Near Infrared Spectroscopy (fNIRS) may be a suitable, simple, and cost-effective brain imaging technique for detecting divergent neuronal patterns at an early stage of neurodegeneration. In course of Mild Cognitive Impairment (MCI) or Alzheimer's disease (AD), a deficit in visual-spatial processing, located in the parietal cortex, is a reliable risk factor. Earlier, we established the application of the clock-hand-angle-discrimination task (ADT) during fNIRS to identify neuronal correlates of the visual-spatial processing in a healthy elderly sample. In this analysis, we aimed to measure and find out differences in the hemodynamic response in MCI participants compared to matched healthy controls. As expected, MCI participants showed more errors over all conditions of pointer length and a higher reaction time in the long and middle pointer length condition. Moreover, results revealed a significant reduction of cortical activation in MCI patients. There was a generally increased activity in both the right as compared to the left hemisphere and the superior parietal brain region as compared to the inferior parietal brain region in both groups. In summary, fNIRS can be implemented in the measurement of visual-spatial processing in MCI patients and healthy elderly based on ADT. MCI participants had difficulties to cope with the ADT. Since neuronal hypoactivity occurs with concomitant behavioral deficits, an additional analysis was performed on a subgroup of MCI patients who performed as well as the control group in behavior. This subgroup analysis also showed a hypoactivation of the parietal cortex, without evidence of a compensatory activation. Therefore, we assume that MCI patients are characterized by a deficit in the parietal cortex. Overall, these findings confirm our hypothesis that hemodynamic deficits in visual-spatial processing, localized in the parietal cortex, are reliable and early diagnostic markers for cognitive decline in risk groups for the development of AD.

Clinico-genetic findings in 509 frontotemporal dementia patients.

Frontotemporal dementia (FTD) is a clinically and genetically heterogeneous disorder. To which extent genetic aberrations dictate clinical presentation remains elusive. We investigated the spectrum of genetic causes and assessed the genotype-driven differences in biomarker profiles, disease severity and clinical manifestation by recruiting 509 FTD patients from different centers of the German FTLD consortium where individuals were clinically assessed including biomarker analysis. Exome sequencing as well as C9orf72 repeat analysis were performed in all patients. These genetic analyses resulted in a diagnostic yield of 18.1%. Pathogenic variants in C9orf72 (n = 47), GRN (n = 26), MAPT (n = 11), TBK1 (n = 5), FUS (n = 1), TARDBP (n = 1), and CTSF (n = 1) were identified across all clinical subtypes of FTD. TBK1-associated FTD was frequent accounting for 5.4% of solved cases. Detection of a homozygous missense variant verified CTSF as an FTD gene. ABCA7 was identified as a candidate gene for monogenic FTD. The distribution of APOE alleles did not differ significantly between FTD patients and the average population. Male sex was weakly associated with clinical manifestation of the behavioral variant of FTD. Age of onset was lowest in MAPT patients. Further, high CSF neurofilament light chain levels were found to be related to GRN-associated FTD. Our study provides large-scale retrospective clinico-genetic data such as on disease manifestation and progression of FTD. These data will be relevant for counseling patients and their families.

Continuous Fusion of Motion Data Using an Axis-Angle Rotation Representation with Uniform B-Spline.

The fusion of motion data is key in the fields of robotic and automated driving. Most existing approaches are filter-based or pose-graph-based. By using filter-based approaches, parameters should be set very carefully and the motion data can usually only be fused in a time forward direction. Pose-graph-based approaches can fuse data in time forward and backward directions. However, pre-integration is needed by applying measurements from inertial measurement units. Additionally, both approaches only provide discrete fusion results. In this work, we address this problem and present a uniform B-spline-based continuous fusion approach, which can fuse motion measurements from an inertial measurement unit and pose data from other localization systems robustly, accurately and efficiently. In our continuous fusion approach, an axis-angle is applied as our rotation representation method and uniform B-spline as the back-end optimization base. Evaluation results performed on the real world data show that our approach provides accurate, robust and continuous fusion results, which again supports our continuous fusion concept.

Motor speech disorders in the nonfluent, semantic and logopenic variants of primary progressive aphasia.

OBJECTIVE: Motor speech disorders (MSDs) are characteristic for nonfluent primary progressive aphasia (nfvPPA). In primary progressive aphasia (PPA) of the semantic (svPPA) and of the logopenic type (lvPPA), speech motor function is considered typically intact. However, knowledge on the prevalence of MSDs in svPPA and lvPPA is mainly based on studies with a priori knowledge of PPA syndrome diagnosis. This fully blinded retrospective study aims to provide data on the prevalence of all types of MSDs in a large sample of German-speaking patients with different subtypes of PPA. METHOD: Two raters, blinded for PPA subtype, independently evaluated connected speech samples for MSD syndrome and severity from 161 patients diagnosed with nfvPPA, svPPA or lvPPA in the database of the German Consortium of Frontotemporal Lobar Degeneration (FTLDc). In case of disagreement, a third experienced rater re-evaluated the speech samples, followed by a consensus procedure. Consensus was reached for 160 patients (74 nfvPPA, 49 svPPA, 37 lvPPA). MAIN RESULTS: Across all PPA syndromes, 43.8% of the patients showed MSDs. Patients with nfvPPA demonstrated the highest proportion of MSDs (62.2%), but MSDs were also identified in svPPA (26.5%) and lvPPA (29.7%), respectively. Overall, dysarthria was the most common class of MSDs, followed by apraxia of speech. In addition, we identified speech abnormalities presenting as "syllabic speech", "dysfluent speech", and "adynamic speech". DISCUSSION: Our study confirmed MSDs as frequently occurring in PPA. The study also confirmed MSDs to be most common in patients with nfvPPA. However, MSDs were also found in substantial proportions of patients with svPPA and lvPPA. Furthermore, our study identified speech motor deficits that have not received attention in previous studies on PPA. The results are discussed against the background of the existing literature on MSDs in PPA, including theoretical considerations of the neuroanatomical conditions described for each of the different subtypes of PPA.

Quantifying progression in primary progressive aphasia with structural neuroimaging.

INTRODUCTION: The term primary progressive aphasia (PPA) sums up the non-fluent (nfv), the semantic (sv), and the logopenic (lv) variant. Up to now, there is only limited data available concerning magnetic resonance imaging volumetry to monitor disease progression. METHODS: Structural brain imaging and an extensive assessment were applied at baseline and up to 4-year(s) follow-up in 269 participants. With automated atlas-based volumetry 56 brain regions were assessed. Atrophy progression served to calculate sample sizes for therapeutic trials. RESULTS: At baseline highest atrophy appeared in parts of the left frontal lobe for nfvPPA (-17%) and of the left temporal lobe for svPPA (-34%) and lvPPA (-24%). Severest progression within 1-year follow-up occurred in the basal ganglia in nfvPPA (-7%), in the hippocampus/amygdala in svPPA (-9%), and in (medial) temporal regions in lvPPA (-6%). CONCLUSION: PPA presents as a left-dominant, mostly gray matter sensitive disease with considerable atrophy at baseline that proceeds variant-specific.

Predicting disease progression in behavioral variant frontotemporal dementia.

INTRODUCTION: The behavioral variant of frontotemporal dementia (bvFTD) is a rare neurodegenerative disease. Reliable predictors of disease progression have not been sufficiently identified. We investigated multivariate magnetic resonance imaging (MRI) biomarker profiles for their predictive value of individual decline. METHODS: One hundred five bvFTD patients were recruited from the German frontotemporal lobar degeneration (FTLD) consortium study. After defining two groups ("fast progressors" vs. "slow progressors"), we investigated the predictive value of MR brain volumes for disease progression rates performing exhaustive screenings with multivariate classification models. RESULTS: We identified areas that predict disease progression rate within 1 year. Prediction measures revealed an overall accuracy of 80% across our 50 top classification models. Especially the pallidum, middle temporal gyrus, inferior frontal gyrus, cingulate gyrus, middle orbitofrontal gyrus, and insula occurred in these models. DISCUSSION: Based on the revealed marker combinations an individual prognosis seems to be feasible. This might be used in clinical studies on an individualized progression model.

Micronucleus frequency in buccal mucosa cells of patients with neurodegenerative diseases.

Neurodegenerative diseases show an increase in prevalence and incidence, with the most prominent example being Alzheimer's disease. DNA damage has been suggested to play a role in the pathogenesis, but the exact mechanisms remain elusive. We enrolled 425 participants with and without neurodegenerative diseases and analyzed DNA damage in the form of micronuclei in buccal mucosa samples. In addition, other parameters such as binucleated cells, karyolytic cells, and karyorrhectic cells were quantified. No relevant differences in DNA damage and cytotoxicity markers were observed in patients compared to healthy participants. Furthermore, other parameters such as lifestyle factors and diseases were also investigated. Overall, this study could not identify a direct link between changes in buccal cells and neurogenerative diseases, but highlights the influence of lifestyle factors and diseases on the human buccal cytome.

Neuronal correlates of the visual-spatial processing measured with functional near-infrared spectroscopy in healthy elderly individuals.

Alzheimer's disease (AD) and Mild Cognitive Impairment (MCI) are a globally rising issue. It is necessary to detect such diseases early to find strategies for prevention. Typically, patients with MCI or AD show deviant neuronal patterns, which could be detected early through brain imaging techniques enabling assumptions about pre-existing diseases. Functional Near-Infrared Spectroscopy (fNIRS) is an appropriate imaging method because of its easy and economical nature with hardly any drawbacks. An early measurable risk factor indicating neurodegenerative processes could be a deficit in visual-spatial processing, which is localized in the parietal cortex. In this study, we aimed to measure the hemodynamic response of the visual-spatial processing in the healthy elderly participants of our long-term Vogel Study with fNIRS during the clock-hand-angle-discrimination task (ADT) to deepen our understanding of healthy brain mechanisms. Our results revealed for our healthy sample a significantly increased neuronal brain activity with increasing task difficulties, namely from the long to the middle to the short clock hand during ADT and significantly higher activation in the right hemisphere compared to the left hemisphere as well as in the superior parietal cortex compared to the inferior parietal cortex. Additionally, our behavioral data demonstrated longer reaction times and more errors with an increasing task requirement. We, therefore, assume that visual-spatial processing can successfully be operationalized with fNIRS for healthy elderly people based on ADT. Further fNIRS analyses are planned to investigate pathological neuronal correlates of visual-spatial function in MCI or AD study participants.

Different CSF protein profiles in amyotrophic lateral sclerosis and frontotemporal dementia with C9orf72 hexanucleotide repeat expansion.

OBJECTIVES: The hexanucleotide repeat expansion in the C9orf72 gene is the most common mutation associated with amyotrophic lateral sclerosis (C9-ALS) and frontotemporal dementia (C9-FTD). Until now, it is unknown which factors define whether C9orf72 mutation carriers develop ALS or FTD. Our aim was to identify protein biomarker candidates in the cerebrospinal fluid (CSF) which differentiate between C9-ALS and C9-FTD and might be indicative for the outcome of the mutation. METHODS: We compared the CSF proteome of 16 C9-ALS and 8 C9-FTD patients and 11 asymptomatic C9orf72 mutation carriers (CAR) by isobaric tags for relative and absolute quantitation. Eleven biomarker candidates were selected from the pool of differentially regulated proteins for further validation by multiple reaction monitoring and single-molecule array in a larger cohort (n=156). RESULTS: In total, 2095 CSF proteins were identified and 236 proteins were significantly different in C9-ALS versus C9-FTD including neurofilament medium polypeptide (NEFM) and chitotriosidase-1 (CHIT1). Eight candidates were successfully validated including significantly increased ubiquitin carboxyl-terminal hydrolase isozyme L1 (UCHL1) levels in C9-ALS compared with C9-FTD and controls and decreased neuronal pentraxin receptor (NPTXR) levels in C9-FTD versus CAR. CONCLUSIONS: This study presents a deep proteomic CSF analysis of C9-ALS versus C9-FTD patients. As a proof of concept, we observed higher NEFM and CHIT1 CSF levels in C9-ALS. In addition, we also show clear upregulation of UCHL1 in C9-ALS and downregulation of NPTXR in C9-FTD. Significant differences in UCHL1 CSF levels may explain diverging ubiquitination and autophagy processes and NPTXR levels might reflect different synapses organisation processes.

Disentangling brain functional network remodeling in corticobasal syndrome - A multimodal MRI study.

OBJECTIVE: The clinical diagnosis of corticobasal syndrome (CBS) represents a challenge for physicians and reliable diagnostic imaging biomarkers would support the diagnostic work-up. We aimed to investigate the neural signatures of CBS using multimodal T1-weighted and resting-state functional magnetic resonance imaging (MRI). METHODS: Nineteen patients with CBS (age 67.0 ± 6.0 years; mean±SD) and 19 matched controls (66.5 ± 6.0) were enrolled from the German Frontotemporal Lobar Degeneration Consortium. Changes in functional connectivity and structure were respectively assessed with eigenvector centrality mapping complemented by seed-based analysis and with voxel-based morphometry. In addition to mass-univariate statistics, multivariate support vector machine (SVM) classification tested the potential of multimodal MRI to differentiate patients and controls. External validity of SVM was assessed on independent CBS data from the 4RTNI database. RESULTS: A decrease in brain interconnectedness was observed in the right central operculum, middle temporal gyrus and posterior insula, while widespread connectivity increases were found in the anterior cingulum, medial superior-frontal gyrus and in the bilateral caudate nuclei. Severe and diffuse gray matter volume reduction, especially in the bilateral insula, putamen and thalamus, characterized CBS. SVM classification revealed that both connectivity (area under the curve 0.81) and structural abnormalities (0.80) distinguished CBS from controls, while their combination led to statistically non-significant improvement in discrimination power, questioning the additional value of functional connectivity over atrophy. SVM analyses based on structural MRI generalized moderately well to new data, which was decisively improved when guided by meta-analytically derived disease-specific regions-of-interest. CONCLUSIONS: Our data-driven results show impairment of functional connectivity and brain structure in CBS and explore their potential as imaging biomarkers.

Unraveling corticobasal syndrome and alien limb syndrome with structural brain imaging.

Alien limb phenomenon is a rare syndrome associated with a feeling of non-belonging and disowning toward one's limb. In contrast, anarchic limb phenomenon leads to involuntary but goal-directed movements. Alien/anarchic limb phenomena are frequent in corticobasal syndrome (CBS), an atypical parkinsonian syndrome characterized by rigidity, akinesia, dystonia, cortical sensory deficit, and apraxia. The structure-function relationship of alien/anarchic limb was investigated in multi-centric structural magnetic resonance imaging (MRI) data. Whole-group and single-subject comparisons were made in 25 CBS and eight CBS-alien/anarchic limb patients versus controls. Support vector machine was used to see if CBS with and without alien/anarchic limb could be distinguished by structural MRI patterns. Whole-group comparison of CBS versus controls revealed asymmetric frontotemporal atrophy. CBS with alien/anarchic limb syndrome versus controls showed frontoparietal atrophy including the supplementary motor area contralateral to the side of the affected limb. Exploratory analysis identified frontotemporal regions encompassing the pre-/and postcentral gyrus as compromised in CBS with alien limb syndrome. Classification of CBS patients yielded accuracies of 79%. CBS-alien/anarchic limb syndrome was differentiated from CBS patients with an accuracy of 81%. Predictive differences were found in the cingulate gyrus spreading to frontomedian cortex, postcentral gyrus, and temporoparietoocipital regions. We present the first MRI-based group analysis on CBS-alien/anarchic limb. Results pave the way for individual clinical syndrome prediction and allow understanding the underlying neurocognitive architecture.